Triple
T29402979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wrecker |
E745699
|
entity |
| Predicate | hasMultipleSuspectsInPlot |
P183722
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: true | Statement: [The Wrecker, hasMultipleSuspectsInPlot, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleSuspectsInPlot Context triple: [The Wrecker, hasMultipleSuspectsInPlot, true]
-
A.
hasMurderer
Indicates that one entity is the person who committed the murder of another entity.
-
B.
hasApproximateNumberOfConspirators
Indicates that an entity is associated with an estimated or approximate count of conspirators involved with it.
-
C.
notableSuspect
Indicates that an individual is a particularly significant or prominent suspect in relation to an event, case, or investigation.
-
D.
hasPoliticalPlot
Indicates that the subject work contains a storyline or narrative element centered on politics, political events, or political power struggles.
-
E.
hasPartInMurderOf
Indicates involvement as a contributing participant in the commission of a murder.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f0a79eb7d081908c67197a5f347e68 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f7a283388c81908e4a9ee3369e8d6f |
completed | May 3, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a224365081908ff6958e3b30bd05 |
completed | May 3, 2026, 7:29 p.m. |
Created at: April 28, 2026, 2:52 p.m.